计算机与数字工程2017，Vol.45Issue(1)：29-33,121,6.DOI:10.3969/j.issn.1672-9722.2017.01.007
基于机器视觉的冻干粉中的异物检测分类技术研究
Detection and Classification of the Foreign Matter of Lyophilized Powder Based on Machine Vision
丁金如 1孟志刚 1杨燕鹤1
作者信息
- 1. 长沙学院数学与计算机科学系 长沙410003
- 折叠
摘要
Abstract
In this paper,digital image processing technology is used to detect and classify the foreign matter of lyophilized powder.In order to more efficiently detect and classify the existing foreign matter in lyophilized powder such as fibers,hair,particles of glass and other visible foreign matter,BP neural network and support vector machine (SVM) algorithms together with principal component analysis (PCA) feature extraction are used to do classification and recognition.Through industrial small sample data simulation,test results show that both methods have good feasibility and practicability.By comparison it is showed that the recognition based on PCA and SVM algorithm is higher than the recognition based on PCA and BP algorithm.关键词
可见异物检测/主成分分析/BP神经网络/支持向量机Key words
inspection of obviously foreign matter/principal component analysis(PCA)/BP neural network/support vector machine(SVM)分类
信息技术与安全科学引用本文复制引用
丁金如,孟志刚,杨燕鹤..基于机器视觉的冻干粉中的异物检测分类技术研究[J].计算机与数字工程,2017,45(1):29-33,121,6.
